code: def test_export_not_asynchronous():
      orig_path = pyunit_utils.locate(
          "bigdata/laptop/citibike-nyc/2013-07.csv"
      )
      pros_hex = h2o.upload_file(orig_path)
  
      def id_generator(
          size=6, chars=string.ascii_uppercase + string.digits
      ):
          return "".join(random.choice(chars) for _ in range(size))
  
      export_path = (
          pyunit_utils.locate("results")
          + "/"
          + "test_export_not_async_"
          + id_generator()
          + ".csv"
      )
  
      h2o.export_file(pros_hex, export_path)
      export_size1 = os.stat(export_path).st_size
  
      pandas_df_exported = pd.read_csv(export_path)
      pandas_df_exported = pandas_df_exported.drop(
          columns=["starttime", "stoptime", "birth year"]
      )  # H2O exports these as timestamps, 'birth year' has a weird NA sequence
      pandas_df_orig = pd.read_csv(orig_path)
      pandas_df_orig = pandas_df_orig.drop(
          columns=["starttime", "stoptime", "birth year"]
      )
  
      pd.testing.assert_frame_equal(pandas_df_orig, pandas_df_exported)
      export_size2 = os.stat(export_path).st_size
  
      # Show that file size didn't change in the mean time => export is not asynchronous
      assert export_size1 == export_size2
  
file_path: h2o-3/h2o-py/tests/testdir_misc/pyunit_export_time_large.py
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  import string
  import random
  import pandas
  import numpy
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: test_export_not_asynchronous() and returns: str